• Journal of the Institute of Electronics Engineers of Korea TC
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• v.42 no.12
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• pp.1-8
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• 2005

In this paper, we study a call admission control algorithm for supporting multicast service under the BcN environment where broadcasting, communication and Internet are converging to be one. It is necessary to control service requests with a certain criteria in order to guarantee QoS because the system capacity is limited. As a possible solution, we divide one multicast service into 3 classes and set up a threshold per each class to control service request. Especially, for the purpose of system benefit, we define system pay-off rate 'GAIN' with the term 'Reward' and 'Penalty' according to admit and reject service request. And we confine the range of threshold which makes GAIN to be maximized. For the performance analysis, we model the system as M/M/m/m queueing system, investigate GAIN under various conditions and show the effectiveness of the proposed algorithm.

• Journal of Communications and Networks
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• v.4 no.3
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• pp.230-245
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• 2002

Usually the network-throughput maximization problem for constant-bit-rate (CBR) circuit-switched traffic is posed for a fixed offered load profile. Then choices of routes and of admission control policies are sought to achieve maximum throughput (usually under QoS constraints). However, similarly to the notion of channel “capacity,” it is also of interest to determine the “network capacity;” i.e., for a given network we would like to know the maximum throughput it can deliver (again subject to specified QoS constraints) if the appropriate traffic load is supplied. Thus, in addition to determining routes and admission controls, we would like to specify the vector of offered loads between each source/destination pair that “achieves capacity.” Since the combined problem of choosing all three parameters (i.e., offered load, admission control, and routing) is too complex to address, we consider here only the optimal determination of offered load for given routing and admission control policies. We provide an off-line algorithm, which is based on Lagrangian techniques that perform robustly in this rigorously formulated nonlinear optimization problem with nonlinear constraints. We demonstrate that significant improvement is obtained, as compared with simple uniform loading schemes, and that fairness mechanisms can be incorporated with little loss in overall throughput.

• The KIPS Transactions:PartA
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• v.10A no.5
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• pp.487-492
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• 2003

To satisfy the requirements for QoS of Users using multimedia content stream service, it is required to control mechanism for QoS based on class priority, URFA classifies the user by two classes (super class, base class) and controls the admission ratio of user's requests by user's class information. URFA increases the admission ratio class and utilization ratio of stream server resources.

• ETRI Journal
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• v.37 no.5
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• pp.917-921
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• 2015

We consider a multiserver system with two classes of customers with preemption, which is a widely used system in the analysis of cognitive radio networks. It is known that the optimal admission control for this system is of threshold type. We express the expected total discounted profit using the total number of customers, thus reducing the stochastic optimization problem with a two-dimensional state space to a problem with a one-dimensional birth-and-death structure. An efficient algorithm is proposed for the calculation of the expected total discounted profit.

• The Transactions of the Korea Information Processing Society
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• v.4 no.8
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• pp.2070-2079
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• 1997

In this paper, we proposed the FNCAC (fuzzy neural call admission control) scheme of the ATM networks which used the benefits of fuzzy logic controller and the learning abilities of the neural network to solve the call admission control problems. The new call in ATM networks is connected if QoS(quality of service) of the current calls is not affected due to the connection of a new call. The neural network CAC(call admission control) system is predictable system because the neural network is able to learn by the input/output pattern. We applied the fuzzy inference on the learning rate and momentum constant for improving the learning speed of the fuzzy neural network. The excellence of the proposed algorithm was verified using measurement of learning numbers in the traditional neural network method and fuzzy neural network method by simulation. We found that the learning speed of the FNCAC based on the fuzzy learning rules is 5 times faster than that of the CAC method based on the traditional neural network theory.

• Journal of Advanced Navigation Technology
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• v.13 no.6
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• pp.901-906
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• 2009

This paper proposes a call admission control(CAC) method for wireless networks, which is based on the upper bound of a possibility distribution of handoff calls dropping rates. The possibility distribution is estimated in a fuzzy inference and a learning algorithm in neural network. The learning algorithm is considered for tuning the membership functions(then parts)of fuzzy rules for the inference. The fuzzy inference method is based on a weighted average of fuzzy sets. The proposed method can avoid estimating excessively large handoff calls dropping rates, and makes possibile self-compensation in real time for the case where the estimated values are smaller than real values. So this method makes secure CAC, thereby guaranteeing the allowed CDR. From simulation studies we show that the estimation performance for the upper bound of call dropping rate is good, and then handoff call dropping rates in CAC are able to be sustained below user's desired value.

• ETRI Journal
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• v.22 no.4
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• pp.40-50
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• 2000

We apply a "sliding-window" Maximum Likelihood(ML) estimator to estimate traffic parameters On-Off source and develop a method for estimating stochastic predicted individual cell arrival rates. Based on these results, we propose a simple Connection Admission Control(CAC)scheme for delay sensitive services in broadband onboard packet switching satellite systems. The algorithms are motivated by the limited onboard satellite buffer, the large propagation delay, and low computational capabilities inherent in satellite communication systems. We develop an algorithm using the predicted individual cell loss ratio instead of using steady state cell loss ratios. We demonstrate the CAC benefits of this approach over using steady state cell loss ratios as well as predicted total cell loss ratios. We also derive the predictive saturation probability and the predictive cell loss ratio and use them to control the total number of connections. Predictive congestion control mechanisms allow a satellite network to operate in the optimum region of low delay and high throughput. This is different from the traditional reactive congestion control mechanism that allows the network to recover from the congested state. Numerical and simulation results obtained suggest that the proposed predictive scheme is a promising approach for real time CAC.

• The Transactions of the Korea Information Processing Society
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• v.4 no.12
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• pp.3150-3158
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• 1997

In the ATM networks, there are two method in traffic control as schemes to improve the quality of service; one is the reactive control after congestion and the other is the preventive control before congestion. The preventive control include the CAC(Connection Admission Control), the UPC(Usage Parameter Control), the NPC(Network Parameter Control) and the PC(Priority co ntrol). In this paper, we propose an efficient UPC algorithm that has a complex structure using the Jumping window algorithm within the Leaky Bucket algorithm. The proposed algorithm controls peak hit rate by the Leaky Bucket algorithm, then it does the traffic control to evaluate by the Jumping Window whether violates mean bit rate or not. As we assume On/Off traffic source model, our simulation results showed cell loss rate less than the pre-existential Leaky Bucket algorithm method, and it could decrease the demanded Bucket size.

• Journal of Communications and Networks
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• v.12 no.6
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• pp.568-576
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• 2010

The paper presents a control architecture aimed at implementing bandwidth optimization combined with call admission control (CAC) over a digital video broadcasting (DVB) return channel satellite terminal (RCST) under quality of service (QoS) constraints. The approach can be applied in all cases where traffic flows, coming from a terrestrial portion of the network, are merged together within a single DVB flow, which is then forwarded over the satellite channel. The paper introduces the architecture of data and control plane of the RCST at layer 2. The data plane is composed of a set of traffic buffers served with a given bandwidth. The control plane proposed in this paper includes a layer 2 resource manager (L2RM), which is structured into decision makers (DM), one for each traffic buffer of the data plane. Each DM contains a virtual queue, which exactly duplicates the corresponding traffic buffer and performs the actions to compute the minimum bandwidth need to assure the QoS constraints. After computing the minimum bandwidth through a given algorithm (in this view the paper reports some schemes taken in the literature which may be applied), each DM communicates this bandwidth value to the L2RM, which allocates bandwidth to traffic buffers at the data plane. Real bandwidth allocations are driven by the information provided by the DMs. Bandwidth control is linked to a CAC scheme, which uses current bandwidth allocations and peak bandwidth of the call entering the network to decide admission. The performance evaluation is dedicated to show the efficiency of the proposed combined bandwidth allocation and CAC.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.8B
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• pp.1141-1149
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• 2010

Next Generation Networks (NGN) is defined as IP-based networks with multi-services and with multi-access networks. A variety of services and access technologies are co-existed within NGN. Therefore there are numerous transport technologies such as Differentiated Services (DiffServ), Multi-protocol Label Switching (MPLS), and the combined transport technologies. In such an environment, flows are aggregated and de-aggregated multiple times in their end-to-end paths. In this research, a method for calculating end-to-end delay bound for such a flow, provided that the information exchanged among networks regarding flow aggregates, especially the maximum burst size of a flow aggregate entering a network. We suggest an admission control mechanism that can decide whether the requested performance for a flow can be met. We further verify the suggested calculation and admission algorithm with a few realistic scenarios.